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Field
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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discover therapeutic targets relevant to Welsh populations. You’ll also help translate your computational insights into lab-based validation using experimental models, paving the way for new diagnostics and
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magnetic actuations under various magnitudes of field activations. These actuation ranges will be planned targeting potential applications in smart vehicles where following targets will be explored, i
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sequences, analyse those data using Bayesian, Maximum Likelihood and coalescence approaches, and build matrices of geolocation and morphological data. The work will be alongside others working on related
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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infectious disease epidemiology and mathematical modelling in Biology and Medicine. Experience in parameter estimation, knowledge of Bayesian methods and computer programming skills would be an advantage. Good
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progression, with the ultimate aim to develop innovative nucleic acid therapeutics against cancer. We make use of advanced molecular and cellular technologies to identify novel targets and get insight
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of Science and Technology (NTNU) offers a joint 3-year PhD fellowship. Novel non-target chemical analyses have recently revealed that groundwater and drinking water are contaminated from PFAS, pesticide and